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richard-churchman
cc0a2bee21
Included open-source Accord.net library code natively to the solution given the deprecated state of that project. Accord.net will be supported inside Jube for own needs (such as upgrading to .Net 7+). Accord.net libraries modified to compile to .Net 6. Modified Accord.net libraries to better support Newtonsoft Json.net serialisation. Included annotations in the Accord.net libraries to house important dependency statistics. Serialised json can be used independently of Jube to recall a Neural Network. Removal of Binary Serializer totally as a precursor to the projects support of .Net 7+. Extensive bug fixing in crucial functions of Neural Network training and recall. While this part of the system remains in Alpha, it is substantially more fit for purpose.
105 lines
3.4 KiB
C#
105 lines
3.4 KiB
C#
// Accord Statistics Library
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// The Accord.NET Framework
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// http://accord-framework.net
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//
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// Copyright © César Souza, 2009-2017
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// cesarsouza at gmail.com
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//
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// This library is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 2.1 of the License, or (at your option) any later version.
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//
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// This library is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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// Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License along with this library; if not, write to the Free Software
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// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
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//
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namespace Accord.Statistics.Testing
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{
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using System;
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using Accord.Statistics.Analysis;
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using Accord.Compat;
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/// <summary>
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/// Hypothesis test for a single ROC curve.
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/// </summary>
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///
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/// <seealso cref="ZTest"/>
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///
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[Serializable]
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public class ReceiverOperatingCurveTest : ZTest
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{
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/// <summary>
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/// Gets the ROC curve being tested.
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/// </summary>
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///
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public ReceiverOperatingCharacteristic Curve { get; private set; }
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/// <summary>
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/// Creates a new <see cref="ReceiverOperatingCurveTest"/>.
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/// </summary>
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///
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/// <param name="curve">The curve to be tested.</param>
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/// <param name="hypothesizedValue">The hypothesized value for the ROC area.</param>
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/// <param name="alternate">The alternative hypothesis (research hypothesis) to test.</param>
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///
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public ReceiverOperatingCurveTest(ReceiverOperatingCharacteristic curve, double hypothesizedValue = 0.5,
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OneSampleHypothesis alternate = OneSampleHypothesis.ValueIsDifferentFromHypothesis)
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{
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this.Curve = curve;
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Compute(curve.Area, hypothesizedValue, curve.StandardError, alternate);
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}
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/// <summary>
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/// Calculates the standard error of an area calculation for a
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/// curve with the given number of positive and negatives instances
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/// </summary>
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///
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public static double HanleyMcNealVariance(double area, int positiveCount, int negativeCount)
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{
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double A = area;
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// real positive cases
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int Na = positiveCount;
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// real negative cases
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int Nn = negativeCount;
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double Q1 = A / (2.0 - A);
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double Q2 = 2 * A * A / (1.0 + A);
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return (A * (1.0 - A) +
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(Na - 1.0) * (Q1 - A * A) +
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(Nn - 1.0) * (Q2 - A * A)) / (Na * Nn);
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}
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/// <summary>
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/// Calculates the standard error of an area calculation for a
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/// curve with the given number of positive and negatives instances
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/// </summary>
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///
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public static double DeLongVariance(double[] positiveAccuracies, double[] negativeAccuracies)
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{
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double[] Vx = positiveAccuracies;
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double[] Vy = negativeAccuracies;
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double varVx = Vx.Variance();
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double varVy = Vy.Variance();
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return varVx / Vx.Length + varVy / Vy.Length;
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}
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}
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}
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